{"id":"W2086325258","doi":"10.1016/j.jmva.2007.01.003","title":"Change detection in autoregressive time series","year":2007,"lang":"en","type":"article","venue":"Journal of Multivariate Analysis","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":111,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Autoregressive model; Mathematics; Estimator; Series (stratigraphy); Statistics; White noise; STAR model; Variance (accounting); Time series; Applied mathematics; Econometrics; Autoregressive integrated moving average","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001284167,0.0003530156,0.0007283825,0.00147152,0.0002897907,0.0009355596,0.0005548854,0.0006488381,0.0009550711],"category_scores_gemma":[0.007451677,0.0002978434,0.0003598807,0.00123813,0.0005104747,0.001045065,0.0005033334,0.0007415006,0.0002224507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002870563,"about_ca_system_score_gemma":0.0002628057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001766656,"about_ca_topic_score_gemma":0.001003447,"domain_scores_codex":[0.999525,0.000110909,0.00002788089,0.0001183409,0.0001480972,0.00006978938],"domain_scores_gemma":[0.9965396,0.002515042,0.0003686934,0.0001804142,0.0003149187,0.00008124107],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001025649,0.0002969442,0.02408248,0.0002599632,0.0002182795,0.0006026637,0.0004266534,0.1696263,0.05428358,0.02700168,0.002859002,0.7193168],"study_design_scores_gemma":[0.00001086355,0.00007422824,0.00901017,0.000009472036,0.0000221427,0.0001394985,0.00003045682,0.9786009,0.005615758,0.00576732,0.0007038699,0.0000152053],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2650867,0.0008971927,0.7316629,0.0002436077,0.0001364428,0.00002602219,0.00008419813,0.0006154272,0.001247509],"genre_scores_gemma":[0.9466717,0.0003632249,0.05117546,0.00004233696,0.00009454156,0.00001441905,0.0001710373,0.00006767569,0.001399752],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001766656,"threshold_uncertainty_score":0.006791413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009226683500178771,"score_gpt":0.2418494691530008,"score_spread":0.232622785652822,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}